Image processing apparatus, image processing system and computer readable medium

ABSTRACT

A computer readable medium storing a program causing a computer to execute a process for image processing, the process includes: inputting first image data as a reference and second image data to be compared with the first image data; selecting a plurality of first sequences from different positions of the first image data, each of the plurality of first sequences includes first unit-image elements; determining whether or not a second sequence including second unit-image elements, having identity in an alignment of shapes with respect to the plurality of first sequences, exists in the second image data; and detecting from the second sequence determined not to exist in the second image data, a unit-image element not having the identity in the alignment of shapes with respect to the first image data among the second image data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2008-165892 filed Jun. 25, 2009.

BACKGROUND

1. Technical Field

The present invention relates to an image processing apparatus, an imageprocessing system and a computer readable medium.

2. Related Art

Digital inspection apparatuses for assisting an inspection processing inwhich image data before correction and image data after the correctionare compared to thereby check whether or not the correction is madecorrectly are known.

SUMMARY

According to an aspect of the invention, A computer readable mediumstoring a program causing a computer to execute a process for imageprocessing, the process includes: inputting first image data as areference and second image data to be compared with the first imagedata; selecting a plurality of first sequences from different positionsof the first image data, each of the plurality of first sequencesincludes first unit-image elements; determining whether or not a secondsequence including second unit-image elements, having identity in analignment of shapes with respect to the plurality of first sequences,exists in the second image data; and detecting from the second sequencedetermined not to exist in the second image data, a unit-image elementnot having the identity in the alignment of shapes with respect to thefirst image data among the second image data.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiment(s) of the present invention will be described indetail based on the following figures, wherein:

FIG. 1 shows a schematic diagram showing an example of the entireconfiguration of the image processing apparatus according to the firstexemplary embodiment of the invention;

FIG. 2A shows a diagram showing an example of an original image;

FIG. 2B shows a diagram showing an example of a target image;

FIG. 3A shows a diagram showing an example of a circumscribed rectangleextracted by a circumscribed rectangle extracting unit;

FIG. 3B shows a diagram showing an example of a character sequencecandidate extracted by a character sequence candidate extracting unit;

FIG. 3C is a diagram showing an example of an original sentencecalculated by a sentence calculation unit;

FIG. 4 shows a diagram for explaining an example of the method ofcalculating a circumscribed rectangle distance;

FIG. 5 shows a diagram for explaining an example of the method ofcalculating a circumscribed rectangle relevance distance;

FIG. 6 shows a flowchart showing an example of the operation forcalculating a determination reference value;

FIG. 7 shows a diagram showing an example of a difference output screen;and

FIG. 8 shows a schematic diagram showing an example of the entireconfiguration of the image processing system according to the secondexemplary embodiment of the invention.

DETAILED DESCRIPTION

The image processing program according to an exemplary embodiment of theinvention is a program causing a computer to execute a process, theprocess comprising: inputting first image data as a reference and secondimage data to be compared with the first image data; selecting aplurality of first sequences from different positions of the first imagedata, each of the plurality of first sequences includes first unit-imageelements; determining whether or not one of a plurality of secondsequences of second unit-image elements, having identity in an alignmentof shapes with respect to the plurality of first sequences, exists inthe second image data; and detecting the one of the second sequencedetermined not to exist in the second image data as a unit-image elementnot having the identity in the alignment of shapes with respect to thefirst image data among the second image data.

The “unit-image element” indicates an image which occupies a region inimage data and contains a character image, for example. The shape of theregion of the unit-image element maybe a rectangle, a circle, an ellipseor other polygon etc., but is not limited thereto. In each of first andsecond exemplary embodiments, the shape of the unit-image element is setas a circumscribed rectangle. Further, the unit-image elements may beregions having the same size or having different sizes from one another.Furthermore, the unit-image element may represent a character imageitself.

The “image data” may be data capable of obtaining information relatingto the unit-image element and the shape of the unit-image element. Forexample, the image data may be data of the raster format such as BMP,TIFF, PNG, GIF, or data of the vector format described by thepage-description language (PDL) etc., or data of the unique format. Theimage data may contain a table, a picture etc., for example, in additionto characters. Further, the image data may contain image data generatedby optically scanning a document.

The “character” is contained as a character image within the image dataand configured by the combination of dots and lines etc. The charactermay be an ideogram such as a numeral or a Chinese character representinga meaning or content in some language or a phonogram such as a Japanesesyllabary or alphabet. The character contains a pictorial symbol, adecorated symbol, a drafting symbol, an electric circuit symbol, a mapsymbol or a meteorological symbol, etc. Further, the character may be aprinting type or a handwritten character.

The “identity in the alignment of shapes” indicates not only the casewhere the first sequence and the second sequence are completely same inthe alignment of the shape and the outward appearance etc. but also thecase where they have the similar shape or high in the similarity, andfurther also the case where the patterns contained in the first andsecond sequences are same or similar.

First Exemplary Embodiment

FIG. 1 is a schematic diagram showing an example of the configuration ofthe image processing apparatus according to the first exemplaryembodiment of the invention. The image processing apparatus 1 isconfigured by an image input unit 10 for inputting two image data of anoriginal image 2 and a target image 3, a sentence obtaining unit 11 forobtaining an original sentence and a target sentence from these twoimage data, a difference obtaining unit 12 for comparing the originalsentence with the target sentence to thereby obtain differentcharacters, a difference output unit 13 acting as an output unit foroutputting the different characters obtained by the difference obtainingunit 12, and first and second storage units 14A, 14B for storingcharacteristic amounts obtained from the original image 2 and the targetimage 3 by the sentence obtaining unit 11, respectively.

The original image 2 is image data containing an original sentence as areference. The target image 3 is image data containing a target sentenceto be compared with the original sentence.

Each of an original sentence and a target sentence is configured by aplurality of character sequences. A character sequence is formed byplural characters. One of an original sentence and a target sentence maybe a typed sentence and the other may be a hand-written sentence.Alternatively, each of an original sentence and a target sentence may bea typed sentence or a hand-written sentence. Further, alternatively, asentence may be formed by typed characters and hand-written characters.

The “different characters” indicates characters which differ in thealignment of shapes between an original sentence and a target sentence,for example, characters changed due to correction, insertion, deletionetc., for example.

(Image Input Unit)

The image input unit 10 inputs an original image 2 and a target image 3as image data designated by a user. The image input unit 10 may beconnected to an image reading device such as a scanner, a digital cameraor a composite machine so as to input image data therefrom.Alternatively, the image input unit 10 may obtain image data from anexternal recording medium such as an optical disk or a semiconductormemory.

(Sentence Obtaining Unit)

The sentence obtaining unit 11 subjects the two image data of theoriginal image 2 and the target image 3 inputted via the image inputunit 10 to a series of image processings to thereby obtain an originalsentence and a target sentence.

That is, the sentence obtaining unit 11 includes a circumscribedrectangle extracting unit 110 for extracting circumscribed rectangleseach containing a character image therein from each of the two imagedata, a circumscribed rectangle characteristic amount calculation unit111 for calculating circumscribed rectangle characteristic amounts foreach of the extracted circumscribed rectangles, a character sequencecandidate extracting unit 112 for extracting a character sequencecandidate formed by a plurality of the circumscribed rectangles, acharacter sequence characteristic amount calculation unit 113 forsubjecting the extracted character sequence candidate to an imagerecognition processing to thereby calculate character sequencecharacteristic amounts, a character sequence determining unit 114 fordetermining whether or not the character sequence candidate is acharacter sequence based on the calculated character sequencecharacteristic amounts, and a sentence calculation unit 115 for couplingthe character sequence candidates each thus determined as a charactersequence to thereby calculate the original sentence and the targetsentence.

The “image recognition processing” is a processing which processingamount is smaller than that of an OCR processing. For example, thisprocessing is a processing for obtaining characteristic informationrelating to a character image contained in the circumscribed rectanglefor each of the circumscribed rectangles constituting the charactersequence candidate. To be concrete, the image recognition processingperforms a pre-processing such as a noise eliminating processing, andthen obtains, as the characteristic information, an average luminance ofpixels, an area and a width of a character image, a distribution of thedirections and the curvatures of edges (contour of the character image)etc. contained in the circumscribed rectangle.

The circumscribed rectangle characteristic amounts include, for example,the characteristic information obtained by the image recognitionprocessing and information such as the position and size of thecircumscribed rectangle in the image data. Further, the charactersequence characteristic amounts include, for example, characteristicinformation of respective circumscribed rectangles constituting thecharacter sequence candidate, and information of the position, size,color and direction (vertical writing, horizontal writing) etc. of thearea where the character sequence candidate is disposed in the imagedata.

(Difference Obtaining Unit)

The difference obtaining unit 12 includes a distance calculation unit120, a distance determining unit 121 and a difference detecting unit122.

The distance calculation unit 120 selects a plurality of first charactersequences from different positions of the original sentence, andcalculates a determination reference value (representative evaluationinformation) for determining whether or not the target sentence includesa second character sequence which has the same alignment of shapes withone of the plurality of the first character sequences thus selected.

In this exemplary embodiment, the distance calculation unit 120calculates distances on a character space based on the circumscribedrectangle characteristic amounts of the circumscribed rectanglesconstituting the first and second character sequences to therebycalculate the determination reference value. The distance on thecharacter space (hereinafter referred to “distance”) is an indexrepresenting whether or not, when comparing characters to each other,the alignments of shapes are same between the characters. The distancebecomes a relatively small value when the characters are determined tobe same. The distance calculation unit 120 may employ various kinds ofdistance calculation methods such as the Euclidean distance or the cityblock distance.

The distance determining unit 121 determines whether or not the secondcharacter sequence exists in the target sentence based on thedetermination reference value thus calculated by the distancecalculation unit 120 and sends the determination result to thedifference detecting unit 122.

The difference detecting unit 122 detects characters of the targetsentence being not same in the alignments of shapes with respect to theoriginal sentence as different characters.

(Difference Output Unit)

The difference output unit 13 is configured by a liquid crystal displayetc., for example, and outputs and displays the different characterobtained by the difference obtaining unit 12 on a screen in a state ofbeing able to compare with the target sentence. The difference outputunit 13 may not output and display the different character but mayoutput to a printer so as to print the different character or write intoa storage device, for example.

(First and Second Storage Units)

Each of the first and second storage units 14A, 14B is configured by aROM, a RAM or a hard disc drive etc.

The first storage unit 14A stores circumscribed rectangle characteristicamounts 140A calculated by the circumscribed rectangle characteristicamount calculation unit 111 based on the original image 2 and charactersequence characteristic amounts 141A calculated by the circumscribedrectangle characteristic amount calculation unit 111 based on theoriginal image. The second storage unit 14B stores circumscribedrectangle characteristic amounts 140B calculated in the similar mannerbased on the target image 3 and character sequence characteristicamounts 141B calculated based on the target image. The first and secondstorage units 14A, 14B may be configured as a single storage unit.

Such the image processing apparatus 1 can be configured by a personalcomputer (PC), a personal digital assistance (PDA) or a mobile phoneetc.

The respective units of the difference obtaining unit 12 are operated inresponse to that a control unit (not shown) having a CPU etc. providedat the image processing apparatus 1 is operated in accordance with animage processing program stored in the storage unit, for example.Further, similarly, the respective units of the sentence obtaining unit11 are operated in response to that the control unit is operated inaccordance with a sentence obtaining program. The image processingprogram and the sentence obtaining program may be configured as a singleprogram.

Operation of the First Exemplary Embodiment

Next, an example of the operation of the image processing apparatus 1according to the exemplary embodiment will be explained with referenceto FIGS. 2A to 7.

(1) Input of Image Data

First, a user designates the original image 2 and the target image 3 andinputs the image data of these two images to the image input unit 10.Then, the image input unit 10 sends the original image 2 and the targetimage 3 thus designated to the circumscribed rectangle extracting unit110.

FIG. 2A is a diagram showing an example of the original image. Theoriginal image 2 is constituted, for example, by a title unit 100 as anarbitrary character sequence, a graphic unit 101 such as a table or apicture, an original sentence unit 102 containing the original document,etc. The original sentence unit 102 is constituted by plural charactersarranged on plural lines. The original image 2 may contain a pluralityof the graphic units 101 and a plurality of the original sentence units102.

FIG. 2B is a diagram showing an example of the target image. The targetimage 3 is an image data which is partially changed from the originalsentence unit 102 of the original image 2 exemplarily shown in FIG. 2A.That is, the target image 3 is constituted not only by the title unit100 and the graphic unit 101 like the original image 2 but also by atarget sentence unit 103 containing the target sentence which ispartially changed from the original sentence by a user, etc.

(2) Obtaining Sentence

The circumscribed rectangle extracting unit 110 of the sentenceobtaining unit 11 subjects the two image data thus inputted to the imageprocessing to thereby extract a plurality of circumscribed rectangleseach containing a region recognized as a character in each of theoriginal sentence unit 102 and the target sentence unit 103.

FIG. 3A is a diagram showing an example of the circumscribed rectangleextracted by the circumscribed rectangle extracting unit 110. Thecircumscribed rectangle extracting unit 110 extracts the circumscribedrectangle 104 for each of the characters constituting the originalsentence within the original sentence unit 102. The circumscribedrectangle extracting unit 110 also extracts the circumscribed rectangles104 within the target sentence unit 103 in the similar manner.

Next, the circumscribed rectangle characteristic amount calculation unit111 calculates the circumscribed rectangle characteristic amounts 140A,140B with respect to each of the circumscribed rectangles 104 extractedfrom the two images. The circumscribed rectangle characteristic amountcalculation unit 111 stores the circumscribed rectangle characteristicamounts 140A, 140B thus calculated into the first and second storageunits 14A, 14B corresponding to the two images respectively, in relationto the circumscribed rectangles 104 as the calculation source. In thisstage, the characteristic information of the circumscribed rectanglecharacteristic amounts is not calculated yet.

Next, the character sequence candidate extracting unit 112 couples aplurality of the circumscribed rectangles 104 extracted by thecircumscribed rectangle extracting unit 110 to thereby extract acharacter sequence candidate configured by the plurality of thecircumscribed rectangles 104. For example, the character sequencecandidate extracting unit 112 extracts the two circumscribed rectangles104 and calculate a distance between these circumscribed rectangles 104from the circumscribed rectangle characteristic amounts. When thedistance is equal to or smaller than a value, the character sequencecandidate extracting unit 112 combines these two circumscribedrectangles 104 to thereby extract one character sequence candidate.Further, when there is another circumscribed rectangle 104 whichdistance from this character sequence candidate is equal to or smallerthan the value, the character sequence candidate extracting unit 112,the another circumscribed rectangle 104 is further coupled to thecharacter sequence candidate.

FIG. 3B is a diagram showing an example of the character sequencecandidates extracted by the character sequence candidate extracting unit112. The character sequence candidate extracting unit 112 couples aplurality of the circumscribed rectangles 104 constituting the originalsentence unit 102 for each line to thereby extract a plurality of thecharacter sequence candidates 105. The character sequence candidateextracting unit 112 also extracts character sequence candidates 105 asto the target image 3 in the similar manner.

Next, the character sequence characteristic amount calculation unit 113subjects each of the character sequence candidates 105 extracted by thecharacter sequence candidate extracting unit 112 to the imagerecognition processing to thereby calculate the character sequencecharacteristic amounts 141A, 141B. Then, the character sequencecharacteristic amount calculation unit 113 stores the calculatedcharacter sequence characteristic amounts in association with thecharacter sequence candidates 105 of the calculation sources into thefirst and second storage units 14A, 14B corresponding to these two imagedata, respectively.

Then, the character sequence characteristic amount calculation unit 113resolves the character sequence characteristic amounts 141A, 141B thuscalculated for each of the circumscribed rectangles 104, and stores therespective characteristic information thus obtained by the resolution inassociation with the circumscribed rectangles 104 into the first andsecond storage units 14A, 14B as the characteristic information of thecharacter sequence characteristic amounts 141A, 141B, respectively.

Thereafter, the character sequence determining unit 114 determineswhether or not the character sequence candidate 105 contains a charactersequence based on the character sequence characteristic amountsextracted by the character sequence characteristic amount calculationunit 113.

Next, the sentence calculation unit 115 combines the character sequencecandidates 105 each of which is determined to contain the charactersequence to thereby calculate the original sentence and the targetsentence. For example, the sentence calculation unit 115 determineswhether or not the character sequence candidates are combined by usingthe positions, sizes, colors, directions etc. of the regions where thecharacter sequence candidates are disposed in the character sequencecharacteristic amounts, and calculates the original sentence and thetarget sentence. Then, the sentence calculation unit 115 sends theoriginal sentence and the target sentence thus calculated to thedifference obtaining unit 12.

FIG. 3C is a diagram showing an example of the original sentencecalculated by the sentence calculation unit 115. The sentencecalculation unit 115 combines the character sequence candidates 105 ofthe respective lines to calculate the original sentence 106. Thesentence calculation unit 115 also calculate the target sentence as tothe target image 3 in the similar manner.

(3) Obtaining Different Character

When the distance calculation unit 120 of the difference obtaining unit12 receives the original sentence and the target sentence calculated bythe sentence calculation unit 115, the distance calculation unit 115reads the circumscribed rectangle characteristic amounts 140A, 140B ofthe respective circumscribed rectangles 104 constituting these sentencesfrom the first and second storage units 14A, 14B.

Then, the distance calculation unit 120 stores, in order to sequentiallyperforming the processing on a circumscribed rectangle unit basis, thecircumscribed rectangle characteristic amounts 140A, 140B thereof intothe respective elements of an original linear list Ro(i) (where, i=1, 2,. . . M, and M represents the number of the characters of the originalsentence) and a target linear list Rt(j) (where, j=1, 2, . . . N, and Nrepresents the number of the characters of the target sentence).

Next, the distance calculation unit 120 calculates determinationreference value Sj (j=1, 2, . . . N) of the respective circumscribedrectangles constituting the target sentence in accordance with aflowchart of FIG. 6.

First, the distance calculation unit 120 initializes a target counter jfor sequentially selecting the first noticed circumscribed rectanglerepresenting one element to be noticed in the target linear list Rt(j)to “1” (S1).

Then, in the similar manner, the distance calculation unit 120initializes an original counter i for sequentially selecting the secondnoticed circumscribed rectangle representing one element to be noticedin the original linear list Ro(i) to “1” (S10).

Next, the distance calculation unit 120 calculates a circumscribedrectangle distance Dij between the first noticed circumscribed rectangleselected by the original counter i and k circumscribed rectangles beforeand after the first noticed circumscribed rectangle and the secondnoticed circumscribed rectangle selected by the target counter j and kcircumscribed rectangles before and after the second noticedcircumscribed rectangle by using the circumscribed rectanglecharacteristic amounts 140A, 140B (S11). This calculation method can berepresented by the following calculation expression.

$\begin{matrix}{D_{ij} = {\sum\limits_{- k}^{k}\left\{ {{{Ro}\left( {i + k} \right)} - {{Rt}\left( {j + k} \right)}} \right\}^{2}}} & \left( {{Numeral}\mspace{14mu} 1} \right)\end{matrix}$

where k denotes number of characters for calculating distance.

FIG. 4 is a diagram for explaining an example of the method ofcalculating the circumscribed rectangle distance. In FIG. 4, each of thefirst and second noticed circumscribed rectangles 107A, 107B is thecircumscribed rectangle of a character “J” and the number k ofcharacters for calculating distance is “2”. Further, the first noticedcircumscribed rectangle 107A and the two circumscribed rectangles eachbefore and after the first noticed circumscribed rectangle are set as afirst circumscribed rectangle sequence (an example first sequence) 108A,and the second noticed circumscribed rectangle 107B and the twocircumscribed rectangles each before and after the second noticedcircumscribed rectangle are set as a second circumscribed rectanglesequence (an example of second sequence) 10B.

In this case, the distance calculation unit 120 calculates a distancebetween the first circumscribed rectangle sequence 108A and the secondcircumscribed rectangle sequence 108B by using the circumscribedrectangle characteristic amounts 140A, 140B of the circumscribedrectangles. To be concrete, the distance calculation unit 120 calculatesdistances based on five sets of the circumscribed rectanglecharacteristic amounts, that is, a set of Ro(i−2) and Rt(j−2), a set ofRo(i−1) and Rt (j−1), a set of Ro (i) and Rt (j), a set of Ro (i+1) andRt (j+1), and a set of Ro (i+2) and Rt (j+2), and then calculates thecircumscribed rectangle distance 200 as a total of these five distances.

Next, the distance calculation unit 120 calculates first and secondrelevance information respectively representing the relevance betweenthe circumscribed rectangles included in the first and secondcircumscribed rectangle sequences 108A, 108B. Then, the distancecalculation unit 120 compares the first and second relevance informationto thereby calculate a circumscribed rectangle relevance distance Eij(S12). This calculation method can be represented by the followingcalculation expression.

$\begin{matrix}{E_{ij} = {\sum\limits_{- k}^{k}\left\{ {\left( {{{Ro}(i)} - {{Ro}\left( {i + k} \right)}} \right)^{2} - \left( {{{Rt}(j)} - {{Rt}\left( {j + k} \right)}} \right)^{2}} \right\}^{2}}} & \left( {{Numeral}\mspace{14mu} 2} \right)\end{matrix}$

FIG. 5 is a diagram for explaining an example of the method ofcalculating the circumscribed rectangle relevance distance. The noticedcircumscribed rectangles and the number k of characters for calculatingdistance in FIG. 5 are same as those of FIG. 4.

In this case, the distance calculation unit 120 calculates respectivedistances between the first noticed circumscribed rectangle 107A and thetwo circumscribed rectangles each before and after the first noticedcircumscribed rectangle as to the first circumscribed rectangle sequence108A by using the circumscribed rectangle characteristic amounts. To beconcrete, the distance calculation unit 120 calculates distances basedon four sets of the circumscribed rectangle characteristic amounts, thatis, a set of Ro (i−2) and R0 (i), a set of Ro (i−1) and Ro (i), a set ofRo (I+1) and Ro (i) and a set of Ro (i+2) and Ro(i), and then calculatesthe first relevance information as a total of these four distances. Adistance obtained from a set of other circumscribed rectangles, forexample, a set of Ro (i−2) and RO (i+2) may be added to the firstrelevance information.

Next, the distance calculation unit 120 also calculates respectivedistances between the second noticed circumscribed rectangle 107B andthe two circumscribed rectangles each before and after the first noticedcircumscribed rectangle as to the second circumscribed rectanglesequence 108B by using the circumscribed rectangle characteristicamounts, and calculates the second relevance information as a total ofthese four distances. Then, the distance calculation unit 120 calculatesa difference between the first and second relevance information tothereby calculate the circumscribed rectangle relevance distance 201.

Then, the distance calculation unit 120 increments the original counteri (S22) and shifts the first noticed circumscribed rectangle 107A in theoriginal linear list Ro (i) by one. As a result, when the content of theoriginal counter i does not exceed the number M of the characters of theoriginal sentence (No in S23), the process returns to step S20.

In contrast, when the content of the original counter i exceeds thenumber M of the characters of the original sentence (Yes in S23), thedistance calculation unit 120 retrieves a target count j where theevaluation value (evaluation information) obtained by adding thecircumscribed rectangle distance Dij and the circumscribed rectanglerelevance distance Eij each calculated in the aforesaid manner becomesminimum. Then, the distance calculation unit 120 calculates thedetermination reference value Sj as the minimum value thus retrieved(S30). This calculation method can be represented by the followingcalculation expression.

S _(j)=min{αD _(ij) +βE _(ij)}  Numeral 3

where α denotes an arbitrary coefficient, β denotes an arbitrarycoefficient.

Then, the distance calculation unit 120 increments the target counter jby one (S22) and shifts the second noticed circumscribed rectangle 107Bin the target linear list Rt(j) by one. As a result, when the content ofthe target counter j does not exceed the number N of the characters ofthe target sentence (No in S32), the process returns to step S10. Incontrast, when the content of the target counter exceeds the number (Yesin S32), the process is terminated.

In the aforesaid manner, the distance calculation unit 120 calculatesthe determination reference value Sj for each of the circumscribedrectangles constituting the target sentence. Then, the distancedetermining unit 121 compares the determination reference value Sjcalculated for each of the circumscribed rectangles with a thresholdvalue (threshold information) to thereby determine whether or not eachof the determination reference values exceeds the threshold value, andoutput the determination results to the difference detecting unit 122.

Next, the difference detecting unit 122 receives the determinationresults from the distance determining unit 121 and detects, when thedetermination reference value is determined to exceed the thresholdvalue, a character contained in the circumscribed rectanglecorresponding to the determination reference value as a differentcharacter.

(4) Display of Difference Output Screen

The difference output unit 13 outputs the different character detectedby the difference detecting unit 122 to the difference output screen.

FIG. 7 is a diagram showing an example of the difference output screen.The difference output screen 15 is provided with a target image displayregion 150 for displaying the target image 3. The target image displayregion 150 displays the circumscribed rectangles detected as thedifferent characters in a state of being surrounded by frames 151A,151B, for example.

The first frame 151A displays that a character “K” is inserted into theoriginal sentence. The second frame 151B displays that a character “R”existed between characters “QS” in the original sentence is deleted. Theunit outside of the frames 151A, 151B may be displayed in a state beingsubjected to the blurring processing, for example. The difference outputscreen 15 may be added with a function of operating the target imagedisplay region 150 such as an enlargement, a reduction or a movement ora function of printing the target image display region 150.

Then, a user visually confirms the difference output screen 15 toconfirm the changed units with respect to the original image 2, that is,the characters within these first and second frames 151A, 151B andchecks whether or not the change is made as intended or the change notbeing intended is contained, for example.

In the aforesaid manner, only different characters are detected in viewof the alignment of characters by comparing character sequences to eachother and displayed on the difference output screen 15.

Second Exemplary Embodiment

FIG. 8 is an entire diagram showing an example of the schematicconfiguration of the image processing system according to the secondexemplary embodiment of the invention. In the first exemplaryembodiment, the image processing apparatus 1 is provided with the threefunctions, that is, the function of inputting the original image 2 andthe target image 3, the difference detection function with respect tothe inputted two images, and display output function of displayingdifferent characters thus detected. In contrast, the image processingsystem 300 according to this exemplary embodiment is configured by animage processing apparatus 1 having the difference detection function, aterminal device 4 having the input function and the display outputfunction, and a network 5 for mutually coupling the image processingapparatus 1 and the terminal device 4. The network 5 is a communicationnetwork such as a LAN (local area network) or the internet.

The terminal device 4 transmits the original image 2 and the targetimage 3 thus inputted to the image processing apparatus 1 via thenetwork 5 and receives screen information as a response from the imageprocessing apparatus 1. Then, the terminal device 4 displays thedifference output screen exemplarily shown in FIG. 7 based on the screeninformation. Such the terminal device 4 may be configured by a personaldigital assistance (PDA) or a mobile phone etc.

The image processing apparatus 1 includes an image input unit whichreceives the original image 2 and the target image 3 via the network 5and a difference output unit which prepares the screen information fordisplaying different characters obtained by a difference obtaining unitand transmits the screen information to the terminal device 4. Asentence obtaining unit, the difference obtaining unit and first andsecond storage potions are configured in the similar manner as those ofthe first exemplary embodiment.

As explained above, the image processing apparatus 1 provides thedifference detection function via the network 5 to the terminal device 4disposed at a different location.

Third Exemplary Embodiment

Although the two image data of the original image 2 and the target image3 is inputted into the image processing apparatus 1 in the firstexemplary embodiment, two text data is inputted into the imageprocessing apparatus 1 in this exemplary embodiment.

The “text data” unit data which is configured by designating a charactersequence and the positions, font, font size etc. of the respectivecharacters and is prepared by an application software such as aword-processing software, presentation software. Thus, the text dataunit data in which a sentence is recorded as data and is not required toobtain sentence data by performing the image recognition processing likeimage data.

The image processing apparatus 1 according to this exemplary embodimentwill be explained with reference to FIG. 1 as to the configurationdifferent from the first exemplary embodiment.

The image input unit 10 of the image processing apparatus 1 inputs anoriginal text and a target text as two text data. Since the originaltext and the target text are data capable of obtaining an originalsentence and a target sentence therefrom, these texts are sent to thedifference obtaining unit 12 without passing through the sentenceobtaining unit 11.

The difference obtaining unit 12 obtains the original sentence and thetarget sentence form the original text and the target text respectivelyand performs the processing similar to that of the first exemplaryembodiment to thereby different characters.

The image input unit 10 may input one image data and one text data. Inthis case, the image data is sent to the sentence obtaining unit 11 andthe text data is sent to the difference obtaining unit 12. Thedifference obtaining unit 12 compares the sentence data obtained by theimage data from the sentence obtaining unit 11 with the sentence datacontained in the text data to thereby obtain different characters.

Other Exemplary Embodiment

The invention is not limited to the aforesaid exemplary embodiments andmay be changed in various manners in a range not departing from the gistof the invention. For example, although, in each of the aforesaidexemplary embodiments, the respective units of the image processingapparatus are realized by the control unit and the image processingprogram, a part or all of them may be realized by a hardware.

Further, the programs used in the aforesaid exemplary embodiments may beread and stored into the storage unit within the apparatus from arecording medium such as a CD-ROM or may be downloaded into the storageunit within the apparatus from a server etc. coupled to a network suchas the internet.

Further, although, in each of the aforesaid exemplary embodiments, eachof the original sentence and the target sentence is prepared by theEnglish language, the original sentence and the target sentence may beprepared by other languages so long as they are prepared by the samelanguage.

Further, although, in each of the aforesaid exemplary embodiments, theidentity of the shapes of characters is determined by using thecharacteristic information obtained by the image recognition processing,the identity of the shapes of characters may be determined by obtaininga difference image of a cut-out image containing characters to becompared and by comparing a threshold value with the total sum of pixelsrecognized as being different in the difference image.

The foregoing description of the exemplary embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Obviously, many modificationsand variations will be apparent to practitioners skilled in the art. Theembodiments were chosen and described in order to best explain theprinciples of the invention and its practical applications, therebyenabling others skilled in the art to understand the invention forvarious embodiments and with the various modifications as are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

1. A computer readable medium storing a program causing a computer toexecute a process for image processing, the process comprising:inputting first image data as a reference and second image data to becompared with the first image data; selecting a plurality of firstsequences from different positions of the first image data, each of theplurality of first sequences includes first unit-image elements;determining whether or not a second sequence including second unit-imageelements, having identity in an alignment of shapes with respect to theplurality of first sequences, exists in the second image data; anddetecting from the second sequence determined not to exist in the secondimage data, a unit-image element not having the identity in thealignment of shapes with respect to the first image data among thesecond image data.
 2. The computer readable medium according to claim 1,wherein the determining includes: extracting first pieces ofcharacteristic information from each of the first unit-image elements;extracting second pieces of characteristic information from each of thesecond unit-image elements; calculating a plurality of pieces ofevaluation information between each of the plurality of first sequencesand the second sequences by using the first and second pieces ofcharacteristic information; and comparing representative evaluationinformation representative of the calculated plurality of pieces ofevaluation information with threshold information.
 3. The computerreadable medium according to claim 1, wherein the determining includes:extracting first pieces of characteristic information from each of thefirst unit-image elements; extracting second pieces of characteristicinformation from each of the second unit-image elements; and comparingthe first pieces of characteristic information and the second piecescharacteristic information at same positions within each of theplurality of first sequences and the second sequences.
 4. The computerreadable medium according to claim 1, wherein the determining includes:extracting first pieces of characteristic information from each of thefirst unit-image elements; extracting second pieces of characteristicinformation from each of the second unit-image elements; calculatingfirst relevance information which represents relevance between the firstunit-image elements contained in each of the plurality of firstsequences based on the first pieces characteristic information;calculating second relevance information which represents relevancebetween the second unit-image elements contained in the second sequencesbased on the second pieces characteristic information; and comparing thecalculated first relevance information and the calculated secondrelevance information.
 5. An image processing apparatus comprising: aninputting unit that inputs first image data as a reference and secondimage data to be compared with the first image data; a selecting unitthat selects a plurality of first sequences from different positions ofthe first image data, each of the plurality of first sequences includesfirst unit-image elements; a determining unit that determines whether ornot a second sequence including second unit-image elements, havingidentity in an alignment of shapes with respect to the plurality offirst sequences, exists in the second image data; and a detecting unitthat detects from the second sequence determined not to exist in thesecond image data, a unit-image element not having the identity in thealignment of shapes with respect to the first image data among thesecond image data.
 6. An image processing system, comprising: aninputting unit that inputs first image data as a reference and secondimage data to be compared with the first image data; a selecting unitthat selects a plurality of first sequences from different positions ofthe first image data, each of the plurality of first sequences includesfirst unit-image elements; a determining unit that determines whether ornot a second sequence including second unit-image elements, havingidentity in an alignment of shapes with respect to the plurality offirst sequences, exists in the second image data; and a detecting unitthat detects from the second sequence determined not to exist in thesecond image data, a unit-image element not having the identity in thealignment of shapes with respect to the first image data among thesecond image data; and an output unit that outputs the unit-imageelement detected by the detecting unit in a state capable of beingcompared with other unit-image elements contained in the second imagedata.